The Methodology Core is linked to two programs, both created within ISR to focus on methodological issues and the integration of cutting-edge methodology into substantive research: the Program in Survey Methodology (PSM), which focuses on survey data collection and estimation methods, and the Quantitative Methodology Program (QMP), which focuses on the methodology and application of quantitative analysis. Both of these programs are highly multidisciplinary. PSM was established at ISR in 1992 to advance social science survey methodology across campus. PSM faculty are internationally known experts in sample design, questionnaire design, estimation of sampling variance from complex sun/eys, interviewing behavior, cognitive processes of respondents, and computerassisted measurement technologies. The program is currently staffed by 13 faculty members (8 PSCaffiliated): Conrad, Couper, Elliott, Groves, Heeringa, Lee, Lepkowski, Little, Raghunathan, Schwarz, Tourangeau, Traugott, and Valliant. Capitalizing on its close ties with the ISR unit responsible for fielding surveys, PSM trains sun/ey methodologists through three interdepartmental degree programs - a certificate, a masters' degree, and a PhD in survey methodology - and a non-candidate for degree option. It also collaborates with the University of Maryland in the Joint Program in Survey Methodology, funded by a consortium of federal statistical agencies to train future generations of survey methodologists. QMP was established at ISR in 1998 to serve as an intellectual hub for interdisciplinary interactions and exchanges on quantitative methodology at UM. Currently, its five core faculty members with offices in QMP - Hansen, Murphy, Narayan, Smith, and Xie -are all PSC- affiliated researchers. Two other active QMP affiliates - Bruch and Harding - are also PSC faculty members. These QMP researchers are experts in a range of methodological areas, including categorical data analysis, survival analysis, longitudinal data analysis, multi-level analysis, spatial-data analysis, causal inference, experimental designs, latent class analysis, latentvariable analysis, data mining, instrumental variable estimation and related methods for quasi-experimental designs, demographic estimation, and micro-simulation (or agent-based modeling).